How to find common key value pairs from within nested dictionaries-CodePudding

I have this nested dictionary

Movies = {1: {'1060277': 'cloverfield', '1877830': 'The Batman', '0117283': 'The Pallbearer'},
          2: {'1877830': 'The Batman', '1877321': 'The Yards', '0117283': 'The Pallbearer'},
          3: {'6723592': 'Tenet', '1099212': 'Twilight', '1877830': 'The Batman'}}

Now i want to return a dictionary that has the common key value pairs from all the dictionaries within the nested dictionary, in this case it would be

--> 1877830 The Batman

As its the only one that's common in all 3 nested dictionaries

What i cant seem to figure out how to compare these dictionaries

#mov is where Movies will be passed    
def Narrow_down(mov):
      final_list= mov[1]
      for i in final_list.keys():
        for x,y in mov.items(): 
            for key in y:
                if i==key:
                    print(i, "is common ")

CodePudding user response：

You basically want to take the first dictionary, and then for every next dictionary, only keep the keys from the first that are also in the next.

A very straightforward solution uses functools.reduce():

from functools import reduce

# you don't really need the outer dictionary, but if you do, this is list(Movies.keys())
movies = [
    {'1060277': 'cloverfield', '1877830': 'The Batman', '0117283': 'The Pallbearer'},
    {'1877830': 'The Batman', '1877321': 'The Yards', '0117283': 'The Pallbearer'},
    {'6723592': 'Tenet', '1099212': 'Twilight', '1877830': 'The Batman'}
]

result = reduce(lambda d1, d2: {k: v for k, v in d1.items() if k in d2 and d2[k] == d1[k]}, movies)

print(result)

Result:

{'1877830': 'The Batman'}

Note that I named the variable movies - you should avoid naming variables with capitals, as that will cause others (and perhaps future you) to assume it's a class name.

CodePudding user response：

You can iterate over the values of the outer dictionary, maintaining a set of key-value pairs that are common to all the dictionaries seen so far (using the set intersection operation). You can then translate this set of key-value pairs into a dictionary using a dictionary comprehension:

common_items = None

for inner_dict in Movies.values():
    if common_items is None:
        common_items = set(inner_dict.items())
    else:
        common_items = common_items.intersection(inner_dict.items())

result = {key: value for key, value in common_items}
print(result)

With the given movies, this prints:

{'1877830': 'The Batman'}

CodePudding user response：

You can use a set intersection of the dictionaries items:

set.intersection(*(set(d.items()) for d in Movies.values()))

Output: {('1877830', 'The Batman')}

As dictionary:

dict(set.intersection(*(set(d.items()) for d in Movies.values())))

Output: {'1877830': 'The Batman'}

CodePudding user response：

If you really only want the common key-value pairs, then here is code that removes the key-value pairs that have the same key but different values for this key:

common_keys: set = None

for _, nested_dict in Movies.items():
    if common_keys is None:
        common_keys = set(nested_dict.keys())
    else:
        common_keys = common_keys.intersection(set(nested_dict.keys()))


# remove key-value pairs with same keys but different values
common_key_value_pairs = {}
common_keys_different_values = set()

for common_key in common_keys:
    for _, nested_dict in Movies.items():
        if common_key in common_key_value_pairs:
            if common_key_value_pairs[common_key] != nested_dict[common_key]:
                common_keys_different_values.add(common_key)
        else:
            common_key_value_pairs[common_key] = nested_dict[common_key]

for key in common_keys_different_values:
    print(f"Key {key} has different values in the respective dicts")
    del common_key_value_pairs[key]
    
print(common_key_value_pairs)